This proposal investigates two emerging structure-based discovery methods: fragment-based lead discovery and homology modeling of targets for inhibitor discovery. I explore several thermodynamic and structural assumptions of these techniques in an effort to reveal their underlying strengths and limitations. The relationship of fragment binding energies to those of larger molecules is uncertain. These concepts will be investigated by "inverse" fragment screening that is, beginning with a known, "drug-like" inhibitor/enzyme complex, breaking the inhibitor into multiple component fragments, and asking if these fragments bind, and where they do so. Will some fragments of known inhibitors not bind due to lack of cooperativity with the rest of the molecule? If these fragments do bind, where do they bind? Do they bind to the same pocket they hit in the larger molecule or is there potential for "hot spots" within active sites that sequester fragments? Finally, can molecular docking be used to rank and predict known binding fragments and if so what will be gained by the vast increase in library size available to docking versus crystallographic soaking methods? The second specific aim addresses the use of homology models in docking, specifically using retrospective docking screens to guide refinement of homology, modeled structures. The use of retrospective docking screens to guide refinement of homology modeled structures is an idea that has never been tried before and may have great implications in the future use of homology models as docking templates. Here I test state-of-the-art homology modeling, in collaboration with Dr. Andrej Sali's laboratory, in a narrow but hopefully deep way. ADC-7 provides us with the perfect model system, to not only see if we can find some inhibitors, but truly do a unprecedented deep and thorough hypothesis driven study of this methodology followed up with subsequent X-ray crystallography to do final comparisons. [unreadable] [unreadable]